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The numerical difference between an observed value and the value predicted by the regression line.
The value or category in a distribution with the highest frequency.
Examples are Cramer’s phi and the correlation coefficient.
Graphic depiction of a bivariate distribution.
Documentation for a data file that usually contains the question wording and responses codes for each variable.
The most commonly used statistical measure of variation.
Shows whether the association in a contingency table is statistically significant.
The middle value in a distribution.
Replacing missing values in data analysis by estimating values from the available data.
Detecting and resolving errors in coding and data entry.
Indicates how much the dependent variable changes for every one-unit increase in the independent variable.
Consists of editing, coding, data entry, and data cleaning.